Abstract 2541: Immune cell clustering in ovarian cancer tumors and its association with survival
Authors: Alex C. Soupir, Christopher M. Wilson, Joellen M. Schildkraut, Lauren C. Peres, Brooke L. Fridley
Journal: Cancer Research (2022)

Abstract New technologies, such as multiplex immunofluorescence microscopy (mIF), are being developed and used for the assessment and visualization of the tumor immune microenvironment (TIME). These assays produce not only an estimate of the abundance of immune cells in the TIME, but also their spatial locations; however, there are currently few approaches to analyze the spatial context of the TIME. Thus, we have developed a framework for the spatial analysis of the TIME using Ripley’s K, coupled with a permutation-based framework to estimate and measure the departure from complete spatial randomness as a measure of the interactions between immune cells. This approach was applied to mIF data collected on tissue microarrays (TMA) and intratumoral regions of interest (ROIs), defined as &amp;gt;90% tumor cells based on pancytokeratin expression and morphology, selected from whole tissue sections from high-grade serous ovarian carcinoma patients (HGSOC) in the African American Cancer Epidemiology Study (94 subjects on TMAs resulting in 263 tissue cores; 93 subjects with 260 ROIs; 27 subjects included in both TMA and ROIs). Cox proportional hazard models, adjusting for stage and age of diagnosis, were constructed to determine the association of abundance and spatial clustering of tumor-infiltrating lymphocytes (TILs; CD3+), cytotoxic T-cells (CD3+ CD8+), and regulatory T-cells (CD3+ FoxP3+) with overall survival. For all models, the referent group was women with no positive cells for the marker of interest. In the analysis of ROIs, HGSOC patients with high abundance and low spatial clustering of TILs (hazard ratio [HR] = 0.069, 95% confidence interval [CI] = 0.01-0.35) and cytotoxic T-cells (HR and CI not estimable as no deaths observed) had the best survival. This finding of better survival in patients with high abundance and low clustering of TILs and cytotoxic T-cells was replicated in the analysis of TMAs (HR = 0.51, 95% CI = 0.31-0.85 for TILs and HR = 0.11, 95% CI = 0.02-0.53 for cytotoxic T-cells). We also demonstrated the models with both abundance and spatial information was more informative than abundance alone (p &amp;lt; 0.01 for CD3+ and CD3+CD8+ in both ROIs and TMAs). High co-localization of regulatory T-cells and cytotoxic T-cells showed best overall survival on both ROI and TMAs (HR=0.49, 95% CI = 0.28-0.88 and HR = 0.42, 95% CI = 0.25-0.71, respectively). The model with spatial co-occurrence information was significantly better than the model with only abundance (p &amp;lt; 0.05). These findings underscore the prognostic importance of evaluating not only immune cell abundance but also the spatial contexture of the immune cells in the ovarian TIME. The use of our framework for spatial analysis of the TIME and immune cell clustering may be applicable in other cancers and provide a novel approach to identification of biomarkers for predicting patient outcomes. Citation Format: Alex C. Soupir, Christopher M. Wilson, Joellen M. Schildkraut, Lauren C. Peres, Brooke L. Fridley. Immune cell clustering in ovarian cancer tumors and its association with survival [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 2541.